Efficient computation offloading using grey wolf optimization algorithm

The widely available smart-phones as well as other mobile devices can be utilized as valuable compute resources with the support of the powerful and elastic paradigm of cloud computing. This is possible by performing computations of a limited scale on mobile devices and migrating or offloading complex services to the cloud. Use of mobile devices for computations will enable a plethora of applications to execute on mobile devices alone without dependence on static infrastructure. However, this entails the cost of transfer of computations to the cloud along with the cost of cloud computing resources. This paper formulates computation offloading as an optimization problem and utilizes nature-inspired approach of Grey Wolf Algorithm (GWO) to achieve near-optimal solutions. Results precisely depict that although the best cost solutions are attained by the brute force technique but the number of computations is significantly higher as compared to Grey Wolf Algorithm. Moreover with the small increase in number of tasks, there is exponential increase in number of computations. Considering these tradeoffs, its more appropriate to use nature-inspired algorithms for computation offloading in a mobile cloud computing environment.